Exploration of the efficacy of radiomics applied to left ventricular tomograms obtained from D-SPECT MPI for the auxiliary diagnosis of myocardial ischemia in CAD

Wang, Junpeng; Fan, Xin; Qin, Shanshan; Shi, Kuangyu; Zhang, Han; Yu, Fei

doi:10.1007/s10554-021-02413-x

Cited by 4 publications

(2 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The post-LC structured feedback and video debriefing consisted of a joined video assessment of the performed LC reflecting on important steps, complications, and potential improvement of the performance of the procedure (exposure, instrument holding, dissection, clip positioning, cutting). Video debriefing consisted of annotating four predefined video frames on an open-source platform using the annotation tool LabelMe [ 35 ]. The four predefined video frames were: starting point of the LC after instrument insertion, first cauterization, identification of the cystic duct and artery, and 10s before clipping.…”

Section: Methodsmentioning

confidence: 99%

Structured feedback and operative video debriefing with critical view of safety annotation in training of laparoscopic cholecystectomy: a randomized controlled study

Cizmic,

Häberle,

Wise

et al. 2024

Surg Endosc

View full text Add to dashboard Cite

Background The learning curve in minimally invasive surgery (MIS) is lengthened compared to open surgery. It has been reported that structured feedback and training in teams of two trainees improves MIS training and MIS performance. Annotation of surgical images and videos may prove beneficial for surgical training. This study investigated whether structured feedback and video debriefing, including annotation of critical view of safety (CVS), have beneficial learning effects in a predefined, multi-modal MIS training curriculum in teams of two trainees. Methods This randomized-controlled single-center study included medical students without MIS experience (n = 80). The participants first completed a standardized and structured multi-modal MIS training curriculum. They were then randomly divided into two groups (n = 40 each), and four laparoscopic cholecystectomies (LCs) were performed on ex-vivo porcine livers each. Students in the intervention group received structured feedback after each LC, consisting of LC performance evaluations through tutor-trainee joint video debriefing and CVS video annotation. Performance was evaluated using global and LC-specific Objective Structured Assessments of Technical Skills (OSATS) and Global Operative Assessment of Laparoscopic Skills (GOALS) scores. Results The participants in the intervention group had higher global and LC-specific OSATS as well as global and LC-specific GOALS scores than the participants in the control group (25.5 ± 7.3 vs. 23.4 ± 5.1, p = 0.003; 47.6 ± 12.9 vs. 36 ± 12.8, p < 0.001; 17.5 ± 4.4 vs. 16 ± 3.8, p < 0.001; 6.6 ± 2.3 vs. 5.9 ± 2.1, p = 0.005). The intervention group achieved CVS more often than the control group (1. LC: 20 vs. 10 participants, p = 0.037, 2. LC: 24 vs. 8, p = 0.001, 3. LC: 31 vs. 8, p < 0.001, 4. LC: 31 vs. 10, p < 0.001). Conclusions Structured feedback and video debriefing with CVS annotation improves CVS achievement and ex-vivo porcine LC training performance based on OSATS and GOALS scores.

show abstract

Section: Methodsmentioning

confidence: 99%

Structured feedback and operative video debriefing with critical view of safety annotation in training of laparoscopic cholecystectomy: a randomized controlled study

Cizmic,

Häberle,

Wise

et al. 2024

Surg Endosc

View full text Add to dashboard Cite

show abstract

“…Moreover, the machine learning model was based on global perfusion abnormalities rather than regional abnormalities. Wang et al [ 22 ] utilized LV tomograms obtained from D-SPECT-MPI for auxiliary diagnosis to assess radiomics methods' feasibility and effectiveness. The predictive models had a sensitivity within [86–91%] and a specificity within [91–95%].…”

Section: Introductionmentioning

confidence: 99%

Post-revascularization Ejection Fraction Prediction for Patients Undergoing Percutaneous Coronary Intervention Based on Myocardial Perfusion SPECT Imaging Radiomics: a Preliminary Machine Learning Study

et al. 2023

View full text Add to dashboard Cite

In this study, the ability of radiomics features extracted from myocardial perfusion imaging with SPECT (MPI-SPECT) was investigated for the prediction of ejection fraction (EF) post-percutaneous coronary intervention (PCI) treatment. A total of 52 patients who had undergone pre-PCI MPI-SPECT were enrolled in this study. After normalization of the images, features were extracted from the left ventricle, initially automatically segmented by k-means and active contour methods, and finally edited and approved by an expert radiologist. More than 1700 2D and 3D radiomics features were extracted from each patient’s scan. A cross-combination of three feature selections and seven classifier methods was implemented. Three classes of no or dis-improvement (class 1), improved EF from 0 to 5% (class 2), and improved EF over 5% (class 3) were predicted by using tenfold cross-validation. Lastly, the models were evaluated based on accuracy, AUC, sensitivity, specificity, precision, and F-score. Neighborhood component analysis (NCA) selected the most predictive feature signatures, including Gabor, first-order, and NGTDM features. Among the classifiers, the best performance was achieved by the fine KNN classifier, which yielded mean accuracy, AUC, sensitivity, specificity, precision, and F-score of 0.84, 0.83, 0.75, 0.87, 0.78, and 0.76, respectively, in 100 iterations of classification, within the 52 patients with 10-fold cross-validation. The MPI-SPECT-based radiomic features are well suited for predicting post-revascularization EF and therefore provide a helpful approach for deciding on the most appropriate treatment.

show abstract

Myocardial D-Spect Image Segmentation Using RSF Model and Kernal Difference Operator

Awan,

Talpur,

Memon

2023

2023 7th International Multi-Topic ICT Conference (IMTIC)

View full text Add to dashboard Cite

Exploration of the efficacy of radiomics applied to left ventricular tomograms obtained from D-SPECT MPI for the auxiliary diagnosis of myocardial ischemia in CAD

Cited by 4 publications

References 26 publications

Structured feedback and operative video debriefing with critical view of safety annotation in training of laparoscopic cholecystectomy: a randomized controlled study

Structured feedback and operative video debriefing with critical view of safety annotation in training of laparoscopic cholecystectomy: a randomized controlled study

Post-revascularization Ejection Fraction Prediction for Patients Undergoing Percutaneous Coronary Intervention Based on Myocardial Perfusion SPECT Imaging Radiomics: a Preliminary Machine Learning Study

Myocardial D-Spect Image Segmentation Using RSF Model and Kernal Difference Operator

Contact Info

Product

Resources

About